Plot the scatter plot of a binary variable with a smoothing curve.
BinaryYScatterPlot( frame, xvar, yvar, title, ..., se = FALSE, use_glm = TRUE, point_color = "black", smooth_color = "blue" )
data frame to get values from
name of the independent column in frame
name of the dependent (output or result to be modeled) column in frame
title to place on plot
no unnamed argument, added to force named binding of later arguments.
if TRUE, add error bars (defaults to FALSE). Ignored if useGLM is TRUE
if TRUE, "smooths" with a one-variable logistic regression (defaults to TRUE)
color for points
color for smoothing line
The points are jittered for legibility. By default, a logistic regression fit is
used, so that the smoothing curve represents the probability of y == 1 (as fit by
the logistic regression). If
use_glm is set to FALSE, a standard smoothing curve (either loess or a
spline fit) is used.
set.seed(34903490) x = rnorm(50) y = 0.5*x^2 + 2*x + rnorm(length(x)) frm = data.frame(x=x,y=y,yC=y>=as.numeric(quantile(y,probs=0.8))) frm$absY <- abs(frm$y) frm$posY = frm$y > 0 frm$costX = 1 WVPlots::BinaryYScatterPlot(frm, "x", "posY", title="Example 'Probability of Y' Plot")